Sr Manager, Software Engineering

Paramount•New York, NY

1d•$150,000 - $185,000

About The Position

Reporting to team leadership, this role manages a project-based team of 3-5 resources building cloud-native media platforms, workflow automation, integrations, and AI-driven production services. The Senior Manager translates management's technical direction into executable engineering plans and owns day-to-day delivery, implementation quality, and production readiness. The role stays hands-on in solution design, code review, and high-risk work, and serves as a senior day-to-day technical lead, maintaining continuity of execution and technical direction.

Requirements

8+ years hands-on software engineering experience building enterprise applications, APIs, or distributed systems.
4+ years managing project-based engineering teams.
Strong development experience in Python or a comparable modern language.
Experience building and operating cloud-native applications on AWS and/or GCP.
Working knowledge of CI/CD, infrastructure as code, automated testing, security, and observability.
Experience managing multiple concurrent engineering workstreams in a production environment.
Demonstrated ability to select, lead, and maintain continuity across contract engineering teams.
Strong communication skills, able to translate technical risk and trade-offs for nontechnical stakeholders, with sound judgment under strain and the ability to influence across teams and vendors without direct authority.

Nice To Haves

Experience with MAM/PAM platforms, metadata management, transcoding, workflow orchestration, or archive systems.
Familiarity with broadcast or enterprise media asset management platforms.
Experience with large-scale content migration and enterprise system integration.
Experience supporting software platforms in a 24/7 broadcast, media, or other mission-critical environment.

Responsibilities

Select, onboard, direct, and evaluate consultant resources; manage vendor performance, project capacity, deliverables, and structured knowledge transfer as assignments change.
Build team depth so delivery and technical knowledge don't sit with one individual.
Stay hands-on in solution design, code review, troubleshooting, and high-risk work.
Translate architecture direction into technical plans, milestones, staffing, and releases.
Own backlog management, estimation, dependencies, scope, delivery risk, and release readiness.
Balance strategic projects, platform improvements, technical debt, and production needs.
Communicate status, risks, and trade-offs to leadership and stakeholders.
Partner with stakeholders to clarify requirements, define technical scope and acceptance criteria, and identify delivery risks before work begins.
Provide day-to-day technical direction within architecture standards set by leadership.
Set expectations for code quality, testing, APIs, documentation, security, and deployment automation.
Promote reusable services and integrations over one-off solutions.
Escalate significant architecture, platform, and vendor decisions to leadership.
Maintain enough architectural depth and institutional knowledge to represent the team's technical direction independently when leadership is unavailable.
Lead delivery of cloud-native services, media workflow integrations, metadata platforms, archive modernization, and content migration initiatives.
Oversee delivery of AI-enabled capabilities for metadata enrichment, content discovery, and workflow automation, including model integration, retrieval systems, data quality, and evaluation, in partnership with architects and AI engineers.
Set standards for responsible use of AI-assisted development tools (Cursor, Claude Code, GitHub Copilot, or equivalent); ensure AI-generated code is reviewed, tested, and documented to normal engineering and security standards.
Ensure appropriate attention to security, identity, cost, monitoring, and supportability across cloud and AI services.
Own production readiness and engineering support for services built by the team.
Ensure monitoring, runbooks, deployment procedures, rollback plans, and escalation paths are in place.
Lead root-cause analysis and corrective action for recurring defects and reliability issues.
Maintain clear boundaries between frontline operational support and engineering escalation.